Identification and Active Exploration of Deformable Object Boundary Constraints through Robotic Manipulation.
Identification and Active Exploration of Deformable Object Boundary Constraints through Robotic Manipulation.
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DOI：
10.1177/0278364914536939
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发表时间：
2014-09
期刊：
影响因子：
--
通讯作者：
Cavusoglu MC
中科院分区：
文献类型：
--
作者：
Boonvisut P;Cavusoglu MC
用于操纵可变形物体的机器人运动规划算法，例如在医疗机器人应用中，依赖于对操纵期间发生的物体变形的准确估计。组织响应的估计（用于离线规划或实时在线重新规划）又需要对象组成参数和边界约束两者的知识。本文提出了一种从机器人操作数据中估计可变形物体边界约束的新算法。该算法利用视觉系统采集的组织变形数据，采用多阶段爬山法来估计物体的边界约束。一个积极的探索技术，它使用的信息最大化的方法，也提出了扩展的识别算法。通过仿真分析了不确定性对所提方法的影响。实验评估的方法的结果也被提出。
Robotic motion planning algorithms for manipulation of deformable objects, such as in medical robotics applications, rely on accurate estimations of object deformations that occur during manipulation. An estimation of the tissue response (for off-line planning or real-time on-line re-planning), in turn, requires knowledge of both object constitutive parameters and boundary constraints. In this paper, a novel algorithm for estimating boundary constraints of deformable objects from robotic manipulation data is presented. The proposed algorithm uses tissue deformation data collected with a vision system, and employs a multi-stage hill climbing procedure to estimate the boundary constraints of the object. An active exploration technique, which uses an information maximization approach, is also proposed to extend the identification algorithm. The effects of uncertainties on the proposed methods are analyzed in simulation. The results of experimental evaluation of the methods are also presented.
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影响因子：
3.8
作者：
Gao, Zhan;Lister, Kevin;Desai, Jaydev P.
通讯作者：
Desai, Jaydev P.
DOI：
10.1115/1.4003620
发表时间：
2011-04-01
影响因子：
1.7
作者：
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通讯作者：
Socrate, Simona
DOI：
10.1115/1.2831031
发表时间：
1996-08-01
影响因子：
4
作者：
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通讯作者：
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影响因子：
7.8
作者：
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通讯作者：
Cavusoglu, M. Cenk
影响因子：
10.9
作者：
Kerdok, AE;Cotin, SM;Dawson, SL
通讯作者：
Dawson, SL